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English(EN) A traffic management system for large and heterogeneous vehicles in narrow industrial environments

新型AGV交通管理系统将工业吞吐量提升11%

本文介绍了一种用于复杂工业环境中自动导引车(AGV)的新型交通管理系统。该系统利用终身多智能体路径查找(L-MAPF)算法结合非均匀有理B样条(NURBS)进行路径生成。它采用改进的边界视界基于冲突的搜索(CBS)算法,并结合滚动视界冲突解决策略,以确保非网格状环境中各种AGV的安全高效运行。实验结果表明,与现有方法相比,吞吐量提高了11%。 AI

影响 该系统可以提高自动化工业物流的效率和安全性,有可能降低运营成本。

排序理由 学术论文,详细介绍了一种针对特定技术问题的新算法和系统。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.MA (Multiagent) 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新型AGV交通管理系统将工业吞吐量提升11%

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学术论文,详细介绍了一种针对特定技术问题的新算法和系统。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Lorenzo Sabattini ·

    面向狭窄工业环境中大型异构车辆的交通管理系统

    The coordination of Automated Guided Vehicles (AGVs) in high-density industrial environments represents a critical challenge within Logistics 4.0, as traditional traffic management methods often lead to inefficiencies caused by negotiation-based priority assignment. To overcome t…